7. Package Development in RStudio | Mastering RStudio: Develop, Communicate, and Collaborate with R

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Mastering RStudio: Develop, Communicate, and Collaborate with R

By : Julian Hillebrand, Nierhoff

4.6 (5)

Mastering RStudio: Develop, Communicate, and Collaborate with R

4.6 (5)

By: Julian Hillebrand, Nierhoff

Overview of this book

RStudio helps you to manage small to large projects by giving you a multi-functional integrated development environment, combined with the power and flexibility of the R programming language, which is becoming the bridge language of data science for developers and analyst worldwide. Mastering the use of RStudio will help you to solve real-world data problems. This book begins by guiding you through the installation of RStudio and explaining the user interface step by step. From there, the next logical step is to use this knowledge to improve your data analysis workflow. We will do this by building up our toolbox to create interactive reports and graphs or even web applications with Shiny. To collaborate with others, we will explore how to use Git and GitHub and how to build your own packages to ensure top quality results. Finally, we put it all together in an interactive dashboard written with R.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. The RStudio IDE – an Overview

1. The RStudio IDE – an Overview

Downloading and installing RStudio

Working with RStudio and projects

Summary

2. Communicating Your Work with R Markdown

2. Communicating Your Work with R Markdown

The concept of reproducible research

Doing reproducible research with R Markdown

Getting started with R Markdown in RStudio

The R Markdown interface

Advanced R Markdown documents

Summary

3. R Lesson I – Graphics System

3. R Lesson I – Graphics System

The graphic system in R

The R graphics package—base

Introducing the lattice package

Introducing ggplot2

Applying The Grammar of Graphics with ggplot2

Using ggplot2

Customizing your charts

Interactive plotting systems

Summary

4. Shiny – a Web-app Framework for R

4. Shiny – a Web-app Framework for R

Introducing Shiny – the app framework

The concept of reactivity

Discovering the scope of the Shiny user interface

Sharing your Shiny application with others

Diving into the Shiny ecosystem

Summary

5. Interactive Documents with R Markdown

5. Interactive Documents with R Markdown

Creating interactive documents with R Markdown

Using R Markdown and Shiny

Embedding interactive charts into R Markdown

Publishing interactive R Markdown documents

Summary

6. Creating Professional Dashboards with R and Shiny

6. Creating Professional Dashboards with R and Shiny

Explaining the concept of dashboards

Introducing the shinydashboard package

Showing the elements of shinydashboard

Building your own KPI dashboard

Summary

7. Package Development in RStudio

7. Package Development in RStudio

Understanding R packages

Installing devtools

Building packages with RStudio

Using Packrat with a project

Writing the documentation for a package

Understanding the namespaces of a package

Building and checking a package

Using roxygen2 for package documentation

Testing a package

Adding a dataset to a package

Writing a package vignette with R markdown

References for further information

Summary

8. Collaborating with Git and GitHub

8. Collaborating with Git and GitHub

Introducing version control

Using Git with RStudio

Using branches

Further resources

Summary

9. R for your Organization – Managing the RStudio Server

9. R for your Organization – Managing the RStudio Server

Managing the RStudio Server

Setting up R, RStudio, and the Shiny Server

Summary

10. Extending RStudio and Your Knowledge of R

10. Extending RStudio and Your Knowledge of R

Extending RStudio, finding answers, and more

RStudio environment customizations

R help is on the way

Improving your R knowledge

Staying up to date in the R world

Summary

Index

Index

Testing a package

When we build a package, it is very important to test it. Packages can get very complex structures and this creates a high potential for bugs. The most basic way to test your package is to build and load it again and again and test all its functions simply by using them. But this only works up to a certain package size. If our package gets too big, we cannot test every single function after every change we made to the package.

The better way to test our packages when they reach a certain size is the testthat package, created by Hadley Wickham, who also created the devtools package. This package is available on CRAN, so we can simply install it with the install.packages() function.

Using testthat in a package

Before we can use testthat in your project, we have to call the use_testthat() function from the devtools package once. This function will set up all folders and dependencies and create the tests folder.

This folder includes a testthat.R file and the testthat folder, which...

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